Evidence suggests that lifestyle changes, concordant with the adoption of agriculture and industrialization, have impacted the emergence of the so-called diseases of modern civilization in humans (e.g. metabolic disorders, cardiovascular disease etc.). The incidence of these diseases in contemporary, industrialized populations is believed to be associated with a lack of adaptation of our genomes to the rapid dietary and lifestyle changes that occurred across human evolution. However the usefulness and resolution of this evolutionary model of disease are limited. Moreover, although the dietary and genetic markers of human evolution have been studied, we still lack understanding on how the microbiome, our second genome, has interacted with nutritional and host- genomic axes to confer increased disease risk in modern humans. Preliminary data by our group show that dietary shifts significantly modulate the gut microbiome and metabolome of wild primates, our closest evolutionary relatives. Additionally, we have identified gut microbiome markers only found in populations representing Paleolithic lifestyles (hunter-gatherers) and distinguishing them from traditional agriculturalists and industrialized populations. Thus, given 1) the potential role of diet in human evolution, 2) the critical impact of the gut microbiome on the nutritional and immune landscape of mammals, and 3) the existence of gut microbiome patterns exclusive of hunter-gatherers, we hypothesize that the emergence of metabolic disease in modern humans was significantly mediated by interactions between diet, the gut microbiome and the human genome across evolution. These issues are still unexplored. Thus, in Aim 1 of this proposal we will use a multi- OMIC approach (gut metabolomics, metagenomics and transcriptomics of the host colonic tissue) to identify metabolic and genetic markers that emerged and/or were lost when humans transitioned from hunter-gatherer to agricultural and industrialized lifestyles, and in humans affected by metabolic disease phenotypes. In Aim 2, we will use integrated meta-OMICs and network theory approaches to predict metabolic disease phenotypes, from hunter-gatherers to, populations in transition to agriculture to modern populations at risk. This system-level study will broaden our understanding of the extrinsic (environmental/nutritional) and intrinsic factors (genetic/metabolic) impacting the evolution of modern human disease. Additionally, the evolutionary approach proposed will shed light on potentially novel diet and microbe-based translational strategies to mitigate the incidence of metabolic disease in contemporary human populations.